All projectsFIELD NOTE 10 / 2026
AI Products & Web SoftwareRAVAND.STUDIO / PROJECT 10

iChatGPT — A Custom ChatGPT-Inspired Interface

iChatGPT is a Persian-first chat interface designed around the client’s needs. A familiar conversation layout brings chat history and AI tools together while leaving room for the product’s own identity and features.

Ravand roleStrategy, design, engineering, and release
EngagementIn development
Accountable team3 people
DeliveredShipped
SPECIMEN / 10202610ROOT / BRANCH / OUTCOMEiChatGPT — A Custom ChatGPT-Inspired Interface
رابط آشنای ChatGPT

A familiar interface for intelligent chat

In development

Engagement

5

Technology & infrastructure

01
ROOT / THE PROBLEM

The problem

The client needed a ChatGPT-familiar interface that could still express the product’s own identity and workflows.

Research, product behavior, and operational data stayed connected through one shared account of the outcome.

CONSTRAINTS OBSERVED
  1. 01Move operational complexity behind one shared model
  2. 02Make impact observable from day one
  3. 03Protect user trust and clarity
02
BRANCH / THE RESPONSE

The response

We translated the ChatGPT mental model into a Persian RTL shell: conversation history, a calm main canvas, and clear inputs for messages and files.

STEP 01

Conversation rail

Fast access to history

STEP 02

Main canvas

Keep attention on the answer

STEP 03

Multimodal input

Text, files, and voice

03
OUTCOME / MEASURED

Measured outcome

Users can enter a conversation without relearning the interface, find history, and continue through familiar product paths.

01

Fast start

02

Familiar pattern

03

Extensible base

SYSTEM MAP / 04 LAYERS

System map

The core loop runs from model selection and message composition to request execution, response display, and history.

LAYER 01

Model choice

Set the conversation context

LAYER 02

Message and file

Compose the input

LAYER 03

Answer and history

Continue the loop

04
PROCESS / In development

Build process

We started with client requirements and familiar ChatGPT patterns, then shaped navigation, response states, and inputs as a component system.

01 / ROOT

Requirement mapping

Define core scenarios

02 / TRUNK

Interface architecture

Shape rail and chat canvas

03 / BRANCH

Interaction detail

States and feedback

Principles

PRINCIPLES / 03
01

Intentional familiarity

Use proven patterns

02

Clarity

One primary action at a time

03

Flexibility

Leave room for capabilities

01
MODULE / RESOURCES

Resources

The experience is defined as a responsive web app so conversations remain continuous across desktop and mobile.

01ConversationsHistory rail and projectsravand.studio02Message spaceMain response canvasravand.studio03ToolsFiles, voice, and modelsravand.studio
02
MODULE / STACK

Technology stack

A Persian RTL web app, component system, and conversation interaction layer form the product foundation.

RTL web app

Persian responsive experience

Component system

Consistent evolution

Conversation interaction

History and inputs

DELIVERY LEDGER

Delivery ledger

The delivered experience combines a ChatGPT-inspired visual language with the client’s custom requirements in an extensible conversation UI.

ChatGPT-inspired UI01
Conversation history02
Extensible base03

The next problem can take root in one clear conversation.

If your problem sits between product, engineering, and growth, let us define it precisely together.

Start a conversation